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Junior dev here.

Goal: Implement a second autogenerated row with one of the projects prefilled out. The first row is blank.

Desired Output

Requirements:

  • The first row of each resource will remain blank.
  • The second row will have a pre-generated project name called "Admin".
  • The rows of each resource must be next to each other.
  • Sort the "Name" row by ASC order.
  • This must be applied to the entire dataset (~900 resources, demo df created for illustration of assistance).

I think I have to do something with a lamda function but I'm not clear on how to fill only 1 row from each resource.

Current Output: I have the table in a pandas Dataframe. The console output is what I have currently.

Current Output

Here's what I have in the script.

import pandas as pd
# Demo DF only
df1 = {
        'Name': ['Julia', 'David'],
        'Project': ['',''],
        'Task': ['',''],
        'Hours': ['','']
      }

df1 = pd.DataFrame(df1, columns=['Name', 'Project', 'Task','Hours'])
df1 = df1.assign(Project="Admin")
df_repeated = pd.concat([df1]*2, ignore_index=True)
df_repeated = df_repeated.sort_values(by=['Name'], ascending=True)
print(df_repeated)
davida28
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2 Answers2

2
pd.concat([df1, df1.assign(Project="Admin")],
          ignore_index=True).sort_values(["Name", "Project"])
#     Name Project Task Hours
# 1  David                   
# 3  David   Admin           
# 0  Julia                   
# 2  Julia   Admin
d.b
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1

You could use numpy's function "where" to either add the "Admin" in every other row:

df1 = pd.DataFrame(df1)
df_repeated = pd.concat([df1]*2, ignore_index=True)
df_repeated = df_repeated.sort_values(by=['Name'], ascending=True, ignore_index=True)
df_repeated['Project'] = np.where(df_repeated.index % 2, 'Admin', '')
d.b
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Neele22
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